Berkeley, CA, May 1, 2019 – Nexilico, a computational biology startup focused on developing in silico tools for microbiome precision medicine, was selected to receive a National Institutes of Health (NIH) Small Business Innovation Research (SBIR) grant for $225,000 to develop a computational platform to predict the individual-specific response of the gut microbiome to therapeutics. This project is in collaboration with Microvi Biotech Inc. and the funding is provided by the National Institute of General Medical Sciences (NIGMS).
The human gut microbiome has recently become a primary focus of therapeutic research. Specifically, evidence for the role of the gut microbiome as a determining factor in drug pharmacokinetics and therapeutics response has exponentially expanded. However, despite extensive progress in gut microbiome research, no current effort had been able to leverage personalized omics data to explore the dynamics of gut microbiome in interacting with therapeutics. Using state-of-the-art computational techniques, Nexilico is developing a predictive computational platform to simulate the personalized, multi-scale dynamics of the gut microbiome in interaction with therapeutics to improve the effectiveness of drug design and development.
About the National Institutes of Health's Small Business Programs: NIH's SBIR and STTR programs are an integral source of capital for early stage U.S. small businesses to engage in federal research and development that has a strong potential for commercialization. These programs invest over 1 billion dollars into health and life science companies that are creating innovative technologies that align with NIH’s mission to improve health and save lives. A key objective is to translate promising technologies to the private sector and enable life-saving innovations to reach consumer markets. To learn more about NIH's Small Business programs, visit: https://sbir.nih.gov/
Disclaimer: Research reported in this press release was supported by National Institute of General Medical Sciences of the National Institutes of Health under award number R43GM130228. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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